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---
license: cc-by-4.0
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': ABE
'1': ART
'2': BAS
'3': BLA
'4': EBO
'5': EOS
'6': FGC
'7': HAC
'8': KSC
'9': LYI
'10': LYT
'11': MMZ
'12': MON
'13': MYB
'14': NGB
'15': NGS
'16': NIF
'17': OTH
'18': PEB
'19': PLM
'20': PMO
splits:
- name: train
num_bytes: 5531894343.482
num_examples: 137093
- name: validation
num_bytes: 688690986.192
num_examples: 17146
- name: test
num_bytes: 691641698.035
num_examples: 17135
download_size: 6935845206
dataset_size: 6912227027.709001
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
task_categories:
- image-classification
- unconditional-image-generation
tags:
- biology
- medical
size_categories:
- 100K<n<1M
---
## About This Dataset
Bone marrow biopsy is procedure applied to collect and examine bone marrow — the spongy tissue inside some of your larger bones.
This biopsy can show whether your bone marrow is healthy and making normal amounts of blood cells. Doctors use these procedures to diagnose and monitor blood and marrow diseases, cancers, as well as fevers of unknown origin.
The dataset contains a collection of over 170,000 de-identified, expert-annotated cells from the bone marrow smears of 945 patients stained using the May-Grünwald-Giemsa/Pappenheim stain. The diagnosis distribution in the cohort included a variety of hematological diseases reflective of the sample entry of a large laboratory specialized in leukemia diagnostics. Image acquisition was performed using a brightfield microscope with 40x magnification and oil immersion.
All samples were processed in the Munich Leukemia Laboratory (MLL), scanned using equipment developed at Fraunhofer IIS and post-processed using software developed at Helmholtz Munich.
## How to Use this dataset
- Create a multi-classification model to predict cell abnormalities;
- Create a binary-classification model to predict if a cell is normal or not.
- Create image generation model to add to training datset
## Acknowledgements
Citation
Matek, C., Krappe, S., Münzenmayer, C., Haferlach, T., & Marr, C. (2021). An Expert-Annotated Dataset of Bone Marrow Cytology in Hematologic Malignancies [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.AXH3-T579
Matek, C., Krappe, S., Münzenmayer, C., Haferlach, T., and Marr, C. (2021). Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image dataset. https://doi.org/10.1182/blood.2020010568
License
CC BY 4.0
https://www.kaggle.com/datasets/andrewmvd/bone-marrow-cell-classification/data
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